reverting to original call order for a simpler change

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>

docs/_static/llama-stack-spec.html

@@ -15610,10 +15610,6 @@
                         "type": "string",
                         "description": "The identifier of the vector database to register."
                     },
-                    "provider_vector_db_id": {
-                        "type": "string",
-                        "description": "The identifier of the vector database in the provider."
-                    },
                     "embedding_model": {
                         "type": "string",
                         "description": "The embedding model to use."
@@ -15628,13 +15624,16 @@
                     },
                     "vector_db_name": {
                         "type": "string",
-                        "description": "The name of the vector database."
+                        "description": "The name of the vector database. :param provider_vector_db_id: The identifier of the vector database in the provider."
+                    },
+                    "provider_vector_db_id": {
+                        "type": "string",
+                        "description": "The identifier of the vector database in the provider."
                     }
                 },
                 "additionalProperties": false,
                 "required": [
                     "vector_db_id",
-                    "provider_vector_db_id",
                     "embedding_model"
                 ],
                 "title": "RegisterVectorDbRequest"

docs/_static/llama-stack-spec.yaml

@@ -10922,10 +10922,6 @@ components:
           type: string
           description: >-
             The identifier of the vector database to register.
-        provider_vector_db_id:
-          type: string
-          description: >-
-            The identifier of the vector database in the provider.
         embedding_model:
           type: string
           description: The embedding model to use.
@@ -10937,11 +10933,16 @@ components:
           description: The identifier of the provider.
         vector_db_name:
           type: string
-          description: The name of the vector database.
+          description: >-
+            The name of the vector database. :param provider_vector_db_id: The identifier
+            of the vector database in the provider.
+        provider_vector_db_id:
+          type: string
+          description: >-
+            The identifier of the vector database in the provider.
       additionalProperties: false
       required:
         - vector_db_id
-        - provider_vector_db_id
         - embedding_model
       title: RegisterVectorDbRequest
     ResumeAgentTurnRequest:

llama_stack/apis/vector_dbs/vector_dbs.py

@@ -68,11 +68,11 @@ class VectorDBs(Protocol):
     async def register_vector_db(
         self,
         vector_db_id: str,
-        provider_vector_db_id: str,
         embedding_model: str,
         embedding_dimension: int | None = 384,
         provider_id: str | None = None,
         vector_db_name: str | None = None,
+        provider_vector_db_id: str | None = None,
     ) -> VectorDB:
         """Register a vector database.
 
@@ -82,6 +82,7 @@ class VectorDBs(Protocol):
         :param embedding_dimension: The dimension of the embedding model.
         :param provider_id: The identifier of the provider.
         :param vector_db_name: The name of the vector database.
+                :param provider_vector_db_id: The identifier of the vector database in the provider.
         :returns: A VectorDB.
         """
         ...

llama_stack/distribution/routers/vector_io.py

@@ -79,20 +79,20 @@ class VectorIORouter(VectorIO):
     async def register_vector_db(
         self,
         vector_db_id: str,
-        provider_vector_db_id: str,
         embedding_model: str,
         embedding_dimension: int | None = 384,
         provider_id: str | None = None,
         vector_db_name: str | None = None,
+        provider_vector_db_id: str | None = None,
     ) -> None:
         logger.debug(f"VectorIORouter.register_vector_db: {vector_db_id}, {embedding_model}")
         await self.routing_table.register_vector_db(
             vector_db_id,
-            provider_vector_db_id,
             embedding_model,
             embedding_dimension,
             provider_id,
             vector_db_name,
+            provider_vector_db_id,
         )
 
     async def insert_chunks(
@@ -126,6 +126,7 @@ class VectorIORouter(VectorIO):
         embedding_model: str | None = None,
         embedding_dimension: int | None = None,
         provider_id: str | None = None,
+        provider_vector_db_id: str | None = None,
     ) -> VectorStoreObject:
         logger.debug(f"VectorIORouter.openai_create_vector_store: name={name}, provider_id={provider_id}")
 
@@ -139,11 +140,11 @@ class VectorIORouter(VectorIO):
 
         vector_db_id = f"vs_{uuid.uuid4()}"
         registered_vector_db = await self.routing_table.register_vector_db(
-            vector_db_id,
             vector_db_id,
             embedding_model,
             embedding_dimension,
             provider_id,
+            provider_vector_db_id,
             name,
         )
         return await self.routing_table.get_provider_impl(registered_vector_db.identifier).openai_create_vector_store(

llama_stack/distribution/routing_tables/vector_dbs.py

@@ -32,12 +32,14 @@ class VectorDBsRoutingTable(CommonRoutingTableImpl, VectorDBs):
     async def register_vector_db(
         self,
         vector_db_id: str,
-        provider_vector_db_id: str,
         embedding_model: str,
         embedding_dimension: int | None = 384,
         provider_id: str | None = None,
+        provider_vector_db_id: str | None = None,
         vector_db_name: str | None = None,
     ) -> VectorDB:
+        if provider_vector_db_id is None:
+            provider_vector_db_id = vector_db_id
         if provider_id is None:
             if len(self.impls_by_provider_id) > 0:
                 provider_id = list(self.impls_by_provider_id.keys())[0]

tests/integration/vector_io/test_vector_io.py

@@ -53,6 +53,7 @@ def test_vector_db_retrieve(client_with_empty_registry, embedding_model_id, embe
         vector_db_id=vector_db_id,
         embedding_model=embedding_model_id,
         embedding_dimension=embedding_dimension,
+        provider_vector_db_id=vector_db_id,
     )
 
     # Retrieve the memory bank and validate its properties
@@ -69,6 +70,7 @@ def test_vector_db_register(client_with_empty_registry, embedding_model_id, embe
         vector_db_id=vector_db_id,
         embedding_model=embedding_model_id,
         embedding_dimension=embedding_dimension,
+        provider_vector_db_id=vector_db_id,
     )
 
     vector_dbs_after_register = [vector_db.identifier for vector_db in client_with_empty_registry.vector_dbs.list()]
@@ -96,6 +98,7 @@ def test_insert_chunks(client_with_empty_registry, embedding_model_id, embedding
         vector_db_id=vector_db_id,
         embedding_model=embedding_model_id,
         embedding_dimension=embedding_dimension,
+        provider_vector_db_id=vector_db_id,
     )
 
     client_with_empty_registry.vector_io.insert(
@@ -131,6 +134,7 @@ def test_insert_chunks_with_precomputed_embeddings(client_with_empty_registry, e
         vector_db_id=vector_db_id,
         embedding_model=embedding_model_id,
         embedding_dimension=embedding_dimension,
+        provider_vector_db_id=vector_db_id,
     )
 
     chunks_with_embeddings = [